Parallel kd-tree with Batch Updates
Summary: Parallel kd-tree (Pkd-tree) for in-memory multi-dimensional data with high parallelism and cache efficiency. Parallel construction and reconstruction-based batch updates (insert/delete) keep the tree weight-balanced, enabling kNN, range, and range-count queries with strong work/span/cache bounds; outperforms baselines; code released. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Ziyang Men (University of California Riverside)
- 2. Zheqi Shen (University of California Riverside)
- 3. Yan Gu (University of California Riverside)
- 4. Yihan Sun (University of California Riverside)
BibTeX Citation
@inproceedings{men_sigmod25,
title = {{Parallel kd-tree with Batch Updates}},
author = {Men, Ziyang and Shen, Zheqi and Gu, Yan and Sun, Yihan},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3709712},
url = {https://dl.acm.org/doi/10.1145/3709712},
year = {2025}
}
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2 | R-Trees: A Dynamic Index Structure For Spatial Searching | 1984 | SIGMOD | 0.0020210012 |
| 8 | The K-D-B-Tree: A Search Structure for Large Multidimensional Dynamic Indexes | 1981 | SIGMOD | 0.00082404462 |
| 461 | Query-based Workload Forecasting for Self-Driving Database Management Systems | 2018 | SIGMOD | 0.00018068441 |
| 2,341 | Parallel R-trees | 1992 | SIGMOD | 8.7233426e-05 |
| 3,685 | Parallel Algorithms for Constructing Range and Nearest-Neighbor Searching Data Structures | 2016 | PODS | 7.2030591e-05 |
| 7,207 | A Scalable and Generic Approach to Range Joins | 2022 | VLDB | 5.6727648e-05 |
| 11,675 | Fast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering* | 2021 | SIGMOD | 5.093636e-05 |
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